Photo-engineered optoelectronic properties of indium tin oxide via reactive laser annealing

Transparent conductive oxides are appealing materials for optoelectronic and plasmonic applications as, amongst other advantages, their properties can be modulated by engineering their defects. Optimisation of this adjustment is, however, a complex design problem. This work examined the modification of the carrier transport properties of sputtered tin-doped indium oxide (ITO) via laser annealing in reactive environments. We relate the optical modifications to the structural, compositional, and electronic properties to elucidate the precise mechanisms behind the reactive laser annealing (ReLA) process. For sufficiently high laser fluence, we reveal an ambient-dependent and purely compositional modulation of the carrier concentration of ITO thin films. Hereby, we demonstrate that ReLA utilises the precise energy delivery of photonic processing to enhance the carrier mobility and finely tune the carrier concentration without significantly affecting the crystal structure. Exploitation of this phenomena may enable one to selectively engineer the optoelectronic properties of ITO, promising an alternative to the exploration of new materials for optoelectronic and photonic applications.


Section A: Thin Film Uniformity
For the seed ITO films, some slight non-uniformity in the thickness and ρ 4pp was present across the 4′′ wafers. This nonuniformity introduces a problem for further LA experiments which require a set of laser-processed "spots" of ~1 × 1 cm across the full wafer. For example, deviations in the seed film may be mistaken for laser-induced modifications from the seed film to the annealed film. To account for this, we investigated into the non-uniformity of the film. After deposition of the ITO films, the wafers were cut into ~90, ~(8 × 8) mm 2 die. The die were cut along their long edge for each cut, into to reduce any stresses introduce to the film. The x and y position, relative to the sample centre, was noted and tracked for each die. Following this, we measured the visible reflectance, R Vis , IR transmittance, T IR , for each die in order to determine the film thickness, d film , "optical" resistivity, ρ opt , "optical" mean free time, τ opt ,and the optical constants, ε 1 and ε 2 . The thickness, as determined from fitting of R Vis , was used to calculate the collinear resistivity, ρ 4pp , from four-point probe (4pp) measurements of the sheet resistance. Furthermore, d film , the UV oscillators, and the high-frequency permittivity, ε ∞ , were fixed during the fitting of IRT data. The properties of each die were plotted against their x and y position to produce a set of colour maps. The deviation is calculated as the percent difference of the die to the average value. We calculate of the "optical" carrier concentration, N opt , and mobility, μ opt , via Eq. 2 and Eq. 3, respectively, from which an understanding of the variations in the transport mechanisms (that are more fundamental properties than the resistivity) can be built. The absolute value of the effective mass (assumed to be to be 0.30 m e ) 1 does not affect the resulting % deviation, but it is important to note that variations in N opt and μ opt may partially originate from variations in m e * . Figure S1a-d presents a colour map of the deviation in (a) d film , (b) ρ opt , (c) N opt , and (d) μ opt , across the 4′′ wafer. In Figure S1a, we observe that the thickness range does not deviate more than 8 nm (7.2%) across the wafer and the standard deviation is only 2 nm (1.8%). It is well known that there exist a thickness dependence on the resistivity of ITO films 2 Furthermore, the change in thickness across the wafer implies a change in the sputtering rate, which has been noted to drastically affect the resulting film properties. 3,4 In Figure S1b, we observe a minor deviation in ρ 4pp across the wafer, where the average resistivity is lower towards the center. From Figure S1c-d, it is found that the decrease in ρ opt towards the centre of the wafer arises primarily from an increase in μ opt from ~15 cm 2 /Vs to nearly twice the edge value of ~25 cm 2 /Vs at the centre. The carrier concentration remains near constant with a value of ~4.2 cm −3 . It is apparent that the change in μ opt gives rise to the decreasing resistivity with sputtering rate. As the film is amorphous across the entire wafer (Section D), structural alterations cannot be used to explain the change in μ opt across the film. Instead, it is noted that for ITO films with N >~4 × 10 20 cm −3 , the dominant scattering mechanism is ionized cluster scattering (ICS) that has a very large scattering coefficient for ITO films and thus the mobility is highly sensitive to N. 5,6 Because of this observed disuniformity across the wafer, the die selected for further processing were limited to an area of the film where the deviation was minimal. In this area, two die were selected to cover the range of resistivity exhibited by this cluster. Figure S1. Colour map of the percentile deviation from the average centre value in (a) the film thickness, d film , and the "optical" (b) resistivity, ρ opt , (c) carrier concentration, N opt , and (d) carrier mobility, μ opt , of the ITO thin film coating across the 4′′ Si wafer Section B: Optical data Figure S2. Fitting report for the "1 st " seed ITO thin film with a resistivity at the upper end of the range exhibited by the seed films selected for further processing: (a) Ψ(E) (blue squares) and Δ(E) (red squares) at incident angles of 55° (darker shade), 60° (normal shade) and 65° (lighter shade). (b) The corresponding IR transmission, T IR (E), (blue squares) and visible reflection, R VIS (E), (red squares). In (a) and (b), the solid green lines indicate the fit to each collected data set. (c) The corresponding, as-fit, real and imaginary parts of the complex permittivity, ε(E) = ε 1 (E) + i 2 (E), (solid red and blue lines, respectively). Note the logarithmic scale in the x-axis of (a), (b) and (c). The vertical dashed black line indicates the boundary between the IR and NIR-VIS-UV ranges covered by the two ellipsometers. Figure S3. Fitting report for the "2 nd " seed ITO thin film with a resistivity at the lower end of the range exhibited by the seed films selected for further processing: (a) Ψ(E) (blue squares) and Δ(E) (red squares) at incident angles of 55° (darker shade), 60° (normal shade) and 65° (lighter shade). (b) The corresponding IR transmission, T IR (E), (blue squares) and visible reflection, R VIS (E), (red squares). In (a) and (b), the solid green lines indicate the fit to each collected data set. (c) The corresponding, as-fit, real and imaginary parts of the complex permittivity, ε(E) = ε 1 (E) + i 2 (E), (solid red and blue lines, respectively). Note the logarithmic scale in the x-axis of (a), (b) and (c). The vertical dashed black line indicates the boundary between the IR and NIR-VIS-UV ranges covered by the two ellipsometers.

Section C: Ellipsometric modelling
Due to the nature of the "inverse problem" of SE, where the sample properties cannot be directly calculated from the measured ellipsometric quantities but the ellipsometry quantities can be calculated from any given sample properties, the precise nature of the fitting is highly dependent on the sample of interest. 7

Oscillator Functions
Lorentz functions produced the best fit when utilised for UV absorption tail. 8 They are described by Eq. (S1): where A L is the oscillator amplitude, E 0 is the centre energy and γ is the broadening of the oscillator. Gaussian functions produced the best fit when used for IR absorption centres. 9 They are described by Eqs. (S2) and (S3).
and the function Γ is a convergence series used to ensure Kramers-Kronig consistency for the real permittivity. 9 The other parameters are defined above.

Justification of SE model
This section outlines the process used to fit SE measurements across the entire IR and NIR-VIS spectral range (0.034 − 3.4 eV) to extract the complex permittivity, ε(E) = ε 1 (E) + iε 2 (E), and optoelectronic properties of the ITO films. A model that considers both the intra-and inter-band absorption is required to fit the optical properties of ITO. To achieve this, we require a "generalised oscillator" model that describes the permittivity of a material as a summation of various individual oscillators . 7 To fit the measurement with a generalised oscillator model, a summation is made of one Drude and one Lorentz oscillator in order to describe both the absorption due to free carriers (intra-band absorption) and inter-band transitions, respectively, as has been suggested by Uprety et al. for ITO films. 10 To improve the fit further, it was necessary to include an additional IR phonon absorption (described by a Gaussian oscillator) at ~0.045 eV. Due to amorphous structure of the ITO film and the screening of the peak by the free carrier absorption, the Sn-O, Sn-O-Sn, and In-O optical phonon modes cannot be individually resolved. 11 The Gaussian oscillator at ~0.045 eV can be said to represent a convolution of the peaks. The final step to accurately fit the NIR-VIS SE data was to include a layer of "optical" surface roughness, described by an effective medium approximation consisting of 50% of the ITO layer below and 50% air.
It is important to note that any fit can be achieved, given enough oscillators. "Over-fitting" of the data in this way can complicate the ability to extract useful information from the generalised oscillator model. Potential over-fitting of the data can be investigated via the parameter correlation, 7 a number between negative and positive unity assigned to each parameter pair where absolute values above 0.90 indicate that the variations in one parameter can be completely accounted for by variations in its correlated counterpart. The parameter correlation can be reduced, increasing the validity of the fit, by reducing the number of free parameters. 1 A general rule is any added complexity in the model (i.e., introducing surface roughness or additional oscillators etc.) is valid if it produces a decrease in the mean-squared error (MSE), which defines how well the data is fit, by at least ~25%. 7 Exceptions to this rule can be made if the parameter is thought to improve the "realness" of the model. To guarantee confidence in the physical reality of the extracted optical constants and optoelectronic parameters, these principles were followed during the optical modelling: ensuring that the utilised model was as simple as possible while producing a good fit to data, with only few and largely uncorrelated fitting parameters, and had been constructed following the guidance of literature. Where possible, the parameters have been verified with independent techniques. For example, the carrier transport properties have been independently measured via Hall Effect. Figure S16 compares the "Hall" (filled symbols) and "optical" (open symbols) (a) carrier concentration, N Hall and N opt respectively, and (b) mobility, μ Hall and μ opt respectively, for the seed ITO films (grey stars) and those subject to reactive laser annealing in 5% H2 in N2 (red circles), 5% O2 in N2 (blue squares), and 100% O2 (green triangles) and between 25 − 125 mJcm −2 in steps of 25 mJcm −2 . Further validation of the resistivity was achieved via four-point probe (Table S1-Table S3) and the gradient in the carrier concentration was independently measured with depth-profile energy-dispersive X-ray spectroscopy ( Figure S20- Figure S22). Hall" (open symbols, dashed lines) and "optical" (filled symbols, solid lines) carrier concentration, N Hall and N opt respectively, for the two seed ITO films (grey stars; S1 with higher resistivity and S2 with lower resistivity) and those subject to reactive laser annealing in 5% H2 in N2 (red circles), 5% O2 in N2 (blue squares), and 100% O2 (green triangles) and between 25 − 125 mJcm −2 in steps of 25 mJcm −2 . (b) "Hall" (open symbols, dashed lines) and "optical" (filled symbols, solid lines) carrier mobility, μ Hall and μ opt respectively, seed ITO films (grey stars) and those subject to reactive laser annealing in 5% H2 in N2 (red circles), 5% O2 in N2 (blue squares), and 100% O2 (green triangles) and between 25 − 125 mJcm −2 in steps of 25 mJcm −2 .
Section D: XRD data and analysis XRD spectra for all ITO films Figure S17. X-ray diffractograms for the two seed ITO films (dark-light grey squares; Seed 1 with higher resistivity and Seed 2 with lower resistivity) and those subject to reactive laser annealing in (a) 100% O2 and (b) 5% H2 in N2 between 25 − 125 mJcm −2 in steps of 25 mJcm −2 (red-blue squares). The fitting of two pseudo-Voigt functions to the asymmetric peak of each film is shown with the solid lines. To facilitate the peak fitting, the (100) Si peak at 32.9⁰ − 33.1⁰ has been manually removed from all diffractograms. Figure S18. X-ray analysis results: (a) Grain size, (b) micro-strain, (c) stress, and (d) area ratio between the two pseudo-Voigt peaks for the two seed ITO films (grey stars; S1 with higher resistivity and S2 with lower resistivity) and those subject to single-pulse reactive laser annealing in O 2 (green triangles; dark green line) and 5% H 2 in N 2 (red circles; dark red line) at 25 − 125 mJcm −2 in steps of 25 mJcm −2 . Figure S19. High resolution (a-b) Sn3d, (c-d) O1s and (e-f) In3d XPS spectra (black dots) for the seed ITO films before and after laser processing with a single pulse at 125 mJcm −2 into an ambient atmosphere of 5% H 2 in N 2 , respectively. The blue, green, cyan, and pink solid lines present the deconvoluted peaks for each corelevel and the red solid line presents the cumulative fit to the data.

EDX data and analysis
The EDX images for the (a) seed ITO film and laser processed with a single 125 mJcm −2 pulse in (b) 5% H 2 in N 2 and (c) O 2 are presented in Figure S20. Across the image, the average emitted X-ray intensity at the characteristic energy of each element within the sample is measured in order to build a depth profile of the relative elemental concentration across the film ( Figure S21). To better compare the films, the intensity of each individual element is normalised to its peak value and the zero-point distance is set to the bottom of the film. This is done by setting the "bottom" of the film to the point where the normalised grey value intensity of In passes 0.2. This value is chosen as it gives a reasonable film bottom that allows each film to align. The normalised grey value intensities for (a) tin, (b) oxygen, (c) indium, (d) platinum and (e) silicon from the defined "bottom" of the seed (grey squares) ITO film and those subject to ReLA at 125 mJcm −2 pulse in 5% H2 in N2 (red squares) and (c) O 2 (green squares) are presented in Figure S22. Figure S20. Transmission Electron Microscopy bright-field cross-sectional images (greyscale) of the (a) seed ITO film and those subject to single-pulse reactive laser annealing at 125 mJcm −2 into a 100 psig pressurised environment of (b) 5% H2 in N2 and (c) 100% O2. The brightfield image is overlayed with images of the detected characteristic X-ray intensity of oxygen (red), indium (green), tin (blue), platinum (purple), and silicon (yellow), as measured via energy-dispersive X-Ray spectroscopy. Figure S21. Depth-profiles of the energy-dispersive X-Ray spectroscopy intensity for the characteristic peaks of oxygen (pink), indium (orange), tin (yellow), platinum (blue), and silicon (purple) for the (a) seed ITO film and those subject to single-pulse reactive laser annealing at 125 mJcm −2 into a 100 psig pressurised environment of (b) 5% H2 in N2 and (c) 100% O2. The green squares present the depth profile of bright-field image greyscale intensity, for reference.

Section F: Opto-thermal simulations
This section contains the results of opto-thermal calculations, performed using a home-built code to elucidate the temperature rise across the structure at time, t, following the laser ignition. We do so by integrating the light propagation properties (optical constants of seed ITO, native SiO2 and Si), in order to define the detailed spatial absorption distribution, A(z), as a function of the distance from the top surface, z. A(z) is presented in Figure S23. Combined with the temporal and spectral profile of the experimental laser ( Figure S24a and Figure S24b, respectively), we are able to solve the one-dimensional (1D) heat transport equation to calculate the temperature transients at each point in the structure. Specifically, the obtained absorption spatial distribution, A(z), and the experimental laser pulse profile, φ(t), are used to determine the laser induced heating source, Q(z, t) = A(z)φ(t), and solved numerically in the 1D heat diffusion equation: 12 c(z)ρ(z) ∂T(z, t) ∂t = ∂ ∂z [k(z)T(z, t) ∂T(z, t) ∂z ] + Q(z, t) (S4) where T(z, t) is the local temperature transient and ρ(z) is the mass density. c(z) is the heat capacity, k(z) is the thermal conductivity (both dependent on z due to the interchange between different materials).
The total laser fluence is given by: and is set here to match the experimental value of 125 mJcm −2 . For simplicity, we assume a linear (i.e., temperature independent) response. In Figure S25a, we present the temperature transient, ΔT(t), in Kelvin at the top (red line) and bottom (blue line) of the ITO film. We used materials properties from literature, as summarised in Table S4.  By studying the linear heat transport regime, one can get insights into the temperature transients and gradients that can be developed, even without considering nonlinear effects on the materials' properties, nor the thermodynamics of phase changes, e.g., melting and re-solidification. Such a temperature gradient (only for the ITO layer) is presented in Figure S25b. The temperature rise at the top of the film is estimated to be ~1000 K, which should be more than sufficient to induce the mobility of oxygen throughout the lattice. Furthermore, we note that the peak temperature rise, ΔT, at the bottom of the film is ~ 80 degrees above room temperature (106.85 °C at the bottom of the film), verifying the 'cold' nature of the LA process and highlighting the applicability of the ReLA process for thin films on thermally sensitive substrates. A final note is that the 1D heat diffusion suffices to describe the temperature gradient in the case of thin films and substrates with high thermal conductivit y. However, when lateral temperature distribution can no longer be ignored, the use of more sophisticated 2D or 3D models become more appropriate.